| Summary: | 碩士 === 國立臺中科技大學 === 資訊工程系碩士班 === 106 === In this study, we adopt support vector machine (SVM) to predict the restaurant sales volume according to the weather information. With climate-related open data of the Central Weather Bureau including the minimum temperature, maximum temperature, average temperature, average rainfall, wind speed, maximum ten minutes, the maximum instantaneous wind, pressure, humidity, average rainfall for several days and sunshine hours, those weather information are used as the attributes of LibSVM to run the analysis of sales volume prediction. The number of monthly sales volume of the restaurant from July of 2014 to June of 2017 are collected from the restaurant in Keelung by combining the weather information from Central Weather Burea as the experimental data for the prediction model.
The results show that support vector machines can accurately predict the weather information for the sales volume of the restaurant. The results can help the restaurant owner to plan good marketing campaigns and reduce inventory costs.
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